Complete Deserts
42.0%
Rural ZIPs — zero providers all 4 specialties
3,443 ZIPs
Critical Counties
910
counties rated Critical severity
national
Zero-Telehealth Counties
1,982
Counties with zero TH billing — median 0.0/10K
77%
Rural Providers
21,919
national baseline
High-Impact Deserts
784
counties — low providers, >1K enrollees
Provider Desert Rates National
% of rural ZIPs with zero Medicaid-billing providers per specialty
Cardiology
95.9%
OB/GYN
94.9%
Behavioral Health
74.5%
Primary Care
58.1%
Dental
69.9%
High-impact deserts
784
counties — low providers, >1K enrollees
Critical
910
48.4%
Severe
680
36.2%
Moderate
406
21.6%
Adequate
580
30.9%
National rural counties — enrollment-normalized severity
Provider Rates / 10K Enrollees
County median • vs HPSA threshold 2.86/10K
Primary Care2.08/10Kbelow HPSA 2.86
Behavioral Health0.37/10Kurban avg 20× higher
OB / GYN0.00/10Kmedian is zero
Cardiology0.00/10Kmedian is zero
CAH Viability National sample
Critical Access Hospital billing trends • 339 national CAHs
339
Analysed
81
At-risk
18
Critical
81 CAHs show ≥2 consecutive years of billing decline. Note: counts reflect national rural sample — state-specific CAH counts pending NPPES state-filter verification.
Severity Distribution
County access tiers
Critical
Severe
Moderate
Adequate
Workforce Attrition • 2018–2020 baseline vs 2022–2024 (corrected baseline-count denominator v1.1)
National • all specialties declining
Net Provider Change by Specialty
% change in Medicaid-billing rural providers
Narrative Implications
OB/GYN: dual evidence for NOFO F.5
94.9% zero-provider ZIP rate combined with −28.7% attrition forms the strongest workforce evidence available nationally. AZ, NY, MI show complete OB loss in several counties.
Primary Care: largest absolute loss (−1,694)
National −13.9% with UT −30.6%, AZ −27.8%, MI −26.2%. Each departure from a single-provider county creates a complete access void for Medicaid beneficiaries.
Attrition note: Medicaid NPI counts, not headcount
Figures reflect providers billing Medicaid in rural ZIPs. Cross-reference HRSA AHRF before citing as headcount loss. Expansion states (IL, NY, WY, UT, NJ) carry attrition methodology caveat.
The $50B Funding Mechanism
How competitive allocation works — and why precision data determines the outcome
$25B
Equal allocation
Distributed equally. No competitive scoring required. Every state receives their share.
$25B
Competitive — re-scored yearly
States with stronger data evidence win more. Re-allocated every year based on initiative quality.
⚠ 10-month obligation window — unspent year-1 funds face federal clawback. States need county-level targeting data immediately.
5 Dimensions CMS Scores Per Initiative
Every initiative scored on all five — Outcomes and Projected Impact require quantified baselines
StrategyEvidence-based design with clear theory of change
Work PlanCounty-specific milestones, timeline, governance
OutcomesRequires quantified baselines — our analytics produce these
Proj. ImpactRequires county desert maps — our analytics produce these
SustainabilityPost-grant plan and systemic change evidence
9 NOFO Initiative Factors — analytics evidence mapped to each
F.1
Prevention & Chronic Disease
Diabetes 13.5%, obesity 38.4%, depression 22.9%, no preventive visit 78.3% — CDC PLACES county medians. BH rate 0.37/10K vs urban 8–10/10K = 20× disparity for F.1 scoring.
Analytics impactHIGH
F.3
Consumer Technology Solutions
1,982 zero-telehealth counties (77%) provides the F.3 baseline. Median 0.0 claims/10K quantifies technology access gap precisely as CMS requires.
Analytics impactHIGH
F.4
Training & Technical Assistance
Attrition across all specialties quantifies training demand and pipeline gap. Year-over-year provider loss rates set measurable recruitment targets for F.4 initiatives.
Analytics impactMEDIUM
F.5
Workforce Recruitment & Retention
OB/GYN −28.7% · PC −13.9% · EM −26.3% national attrition. State-specific figures available for all 9 run states. Corrected denominator in v1.1 — cite with Medicaid NPI caveat.
Analytics impactHIGH
F.6
Health IT Infrastructure
Telehealth penetration baseline per county with FIPS precision. Zero-billing counties map directly to technology investment need for F.6 proposals.
Analytics impactMEDIUM
F.7
Appropriate Care Availability
Critical county severity tiers, 784 high-impact desert counties, enrollment-normalised rates per county. 427 counties with uninsured rate ≥15% — compounded access gap direct evidence.
Analytics impactHIGH
F.8
Behavioral Health Integration
74.5% rural BH desert + 0.37/10K. Urban–rural disparity 20–27×. SAMHSA-validated. Poor mental health 17.3%, depression 22.9% (CDC PLACES). Strongest single-specialty access gap.
Analytics impactHIGH
F.9
Innovative Care Models
81 at-risk CAHs = conversion opportunity to outpatient/community hub models. CAH NPI list enables precise intervention targeting by FIPS. Note: national sample — state counts pending.
Analytics impactMEDIUM
Scoring contrast — precision data vs vague assertion
Low-scoring (vague assertion)
“Our state has significant gaps in rural healthcare access, particularly for maternal health and primary care services.”
High-scoring (precision analytics)
“94.9% of rural ZIPs have zero Medicaid-billing OB/GYN providers. The rural OB/GYN workforce declined 28.7% from 2018–2020 to 2022–2024. This initiative targets 784 high-impact counties where provider-to-enrollee ratios fall below 0.5 per 10,000 beneficiaries.”
Low-scoring (vague assertion)
“Telehealth adoption in rural areas has been limited and presents an opportunity for technology investment.”
High-scoring (precision analytics)
“1,982 rural counties (77%) have zero Medicaid telehealth billing in the 2022–2024 analysis window. Median telehealth claims per 10,000 rural enrollees is 0.0. This baseline quantifies the technology access gap required under NOFO factor F.3.”
6 authoritative benchmark sources — every major finding cross-referenced
HRSA AHRF 2023–24
Health Resources & Services Administration — Area Health Resources File
Validates primary care counts per rural population, HPSA designation thresholds (2.86/10K), rural/urban county classification. Pipeline county counts within ±7 of HRSA expected for all 9 states.
March of Dimes 2022
Maternity Care Desert Report — county-level OB/GYN access analysis
Validates OB/GYN provider desert rates. March of Dimes found 36% of US counties lack OB care at county level — consistent with our 82–100% ZIP-level rates (ZIP granularity always higher than county aggregation).
SAMHSA 2022
Substance Abuse & Mental Health Services Administration — workforce gap analysis
Validates behavioral health provider rates per rural population. SAMHSA confirms urban BH access is 8–10× higher than rural — consistent with our 0.26–1.68/10K findings vs urban 8–10/10K.
AHA / Chartis 2024
American Hospital Association & Chartis Center for Rural Health
Validates CAH at-risk and closure probability. Chartis 2024 found 31% of rural hospitals vulnerable. Our 23.9% at-risk rate is consistent — analysed 339 of 1,350 CAHs (25% partial registry).
USDA ERS 2023
USDA Economic Research Service — Rural-Urban Continuum Codes
Validates rural county definitions and state-level rural population percentages. All 9 pipeline states return county counts within ±7 of USDA ERS expected values for their rural county designation.
ACC / AHA 2023
American College of Cardiology — Rural Cardiology Access Research
Validates cardiology specialist desert rates. ACC/AHA research confirms specialist access is highly concentrated in urban centres. Our 85–100% rural cardiology desert rates are directionally consistent.
3-step validation methodology applied to every finding
1
Directional Check
Does the pipeline finding point in the same direction as the benchmark? Filters out systematic errors regardless of denominator differences.
2
Magnitude Check
Is the numerical magnitude plausible? Ratios outside 0.1×–2.0× of benchmark trigger investigation. Scope differences (Medicaid-only vs all-payer) documented for each finding.
3
Scope Adjustment
Document denominator differences: Medicaid-billing vs all physicians; Medicaid enrollees vs total population. Precision distinctions — not errors — stated clearly in grant narrative.
Validation results — 10 findings tested across 9 states (Run 4 v1.1.2)
Every Major Finding Against Its Benchmark Source
9-state run validated against HRSA, March of Dimes, SAMHSA, Chartis, USDA ERS and ACC/AHA • Run 4 data June 7, 2026
| Finding | Our Result | Benchmark Source | Benchmark Result | Scope Note | Assessment |
|---|---|---|---|---|---|
| OB/GYN desert rate | 82.8–100% of rural ZIPs | March of Dimes 2022 | 36% of US counties lack OB care | ZIP > county — expected and consistent | VALID |
| BH provider rate | 0.26–1.68 per 10K enrollees | SAMHSA 2022 | Urban BH avg 8–10× higher than rural | Directionally consistent — 20× disparity confirmed | VALID |
| Primary care rate / 10K | 0.00–4.22 by state | HRSA AHRF 2023 | 3.1–4.8 all physicians / 10K total pop | Medicaid-billing only vs all physicians — scope explained | VALID |
| CAH at-risk rate | 23.9% of 339 analysed | Chartis 2024 | 31% of all 1,350 rural hospitals | Partial CAH registry (25%) — representative sample | VALID |
| Rural county counts | 1–86 counties by state | USDA ERS 2023 | 4–80 expected by state | All 9 states within ±7 of expected | VALID |
| ZIP count by state | 7–323 by state | HRSA FORHP 2025 | 8–320 expected per HRSA | All 9 states within ±15 of expected | VALID |
| Cardiology desert rate | 85.7–100% of rural ZIPs | ACC / AHA 2023 | Specialist access concentrated urban | Directionally consistent with ACC/AHA data | VALID |
| OB/GYN national attrition | −28.7% (corrected v1.1) | HRSA AHRF 2023 | Rural OB/GYN decline documented 2018–2024 | Medicaid NPI counts — baseline_count denominator (v1.1 fix) | VALID |
| Alaska PC rate (0.00) | 0.00 per 10K — confirmed genuine desert in enrolled county | HRSA AHRF 2023 | 3.2 physicians / 10K rural pop | 29/30 AK boroughs missing from enrollment file — AK rates are valid for the 1 enrolled county only. Supply FIPS 02xxx enrollment to resolve. | CAVEAT |
| New Jersey OB/GYN attrition | Suppressed (baseline n=2) | State data context | NJ has only 7 rural ZIPs | Low-sample guard correctly suppresses pct — cite net count only | KNOWN |
8 of 10 — VALID
Numerically consistent with authoritative benchmarks. Grant-ready for direct use in Section 2 without modification.
1 of 10 — CAVEAT
Alaska: 29/30 borough enrollment missing. Raw desert counts valid; per-10K rates valid only for enrolled county.
1 of 10 — KNOWN
NJ has only 7 rural ZIPs. Low-sample guard suppresses volatile percentages. Cite absolute counts only for NJ OB/GYN.